Creative agents: Simulating the systems model of creativity with generative agents
Naomi Imasato et al.
Abstract
With the growing popularity of generative AI for images, video, and music, we witnessed models rapidly improve in quality and performance. However, not much attention is paid towards enabling AI’s ability to “be creative”. We often attribute the quality of “being creative” to an individual or an object, but we believe that countless variables participate in determining what or who is creative, transcending a single entity or artifact. Csikszentmihalyi’s systems model of creativity suggests that creativity is a product of interactions among multiple parts of a society that create, evaluate, and record. In this study, we implemented and simulated Csikszentmihalyi’s systems model of creativity using virtual agents utilizing large language models (LLMs) and text prompts. We conducted experiments in virtual settings where creativity is achieved with the presence of specific characteristics in the artifact. For comparison, the simulations were conducted with two “virtual artists” being 1)in the system, which received feedback from the field, and 2)isolated, which did not. Both agents were compared by analyzing the novelty, which was measured via Creativity Implication Network, and value, quantified through the desired characteristics present in artifacts. Our results suggest that the agents that receive feedback from the field can generate artifacts that are more novel and more valuable, thus more creative, in the framework of the systems model of creativity. Furthermore, the difference becomes more evident when external factors enact changes to the domain.
Relevance Assessment
Research Gap
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